What is Answer Engine Optimisation?

The full definition

Answer Engine Optimisation (AEO) is the discipline of making your website easy for AI-powered search engines to read, understand, quote, and attribute. Where classic SEO optimises a page to rank inside a list of links, AEO optimises a page (and the wider site) to be cited inside an AI-generated answer.

The set of “answer engines” that matter today includes ChatGPT (with web browsing), Claude, Perplexity, Google AI Overviews, Bing’s Copilot, and increasingly Apple Intelligence. Each of these engines either retrieves live web content, draws on indexed snapshots, or both. Your job in AEO is to be the source they pull from when a user asks a question your business should be the answer to.

What AEO is not

AEO is not a replacement for SEO — it sits on top of it. The same foundations matter: fast pages, clean schema, sensible URL structure, crawlable HTML, and content that genuinely answers user intent. A site that fails at SEO will almost always fail at AEO.

AEO is also not a magic wand. You can’t bolt AEO onto a slow, badly-structured WordPress site and expect immediate citations. Most AEO engagements involve restructuring existing content, deploying complete Schema.org coverage, publishing new files (/llms.txt, /llms-full.txt), and building out a content engine that targets specific high-volume LLM queries.

What AEO actually involves

A typical AEO project covers four work streams:

1. Technical foundations — schema.org coverage on every page (Organization, LocalBusiness, Service, Article, FAQPage, Person), correct robots.txt with explicit allowlists for AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, OAI-SearchBot), and /llms.txt + /llms-full.txt published.
2. Content restructuring — existing pages rewritten in a question-led format. Each section starts with a real question a human would ask, followed by a direct answer in 50–100 words, then 3–5 paragraphs of supporting detail. Bullet points used sparingly because LLMs prefer paragraphs they can quote.
3. Authority signals — Person schema for authors, sameAs links to LinkedIn/YouTube/GitHub, real bylines on every piece of content, last-updated dates visible. AI engines weight authorship heavily when deciding whose content to cite.
4. Answer pages — a dedicated /answers/ section where each page targets one specific LLM-style question. Each page becomes a citation magnet for that question over time.

How AEO success is measured

Three metrics matter: AI citation rate (how often your site is named in answers across ChatGPT, Claude, Perplexity, and Google AI Overviews for target queries), classic search visibility (because AI engines still draw heavily on Google’s index), and qualified inbound traffic and leads from those engines.

Citations are tracked manually with screenshots — there’s no perfect tool for this yet, though several are emerging. Reports are typically monthly with the queries tested, the answers given, and which sources the AI named. Where you’re cited, you know it’s working. Where you’re not, you know what to fix next.

Why AEO matters now

AI search is no longer a side feature. Google AI Overviews now sit above traditional results for an estimated 30%+ of UK queries. ChatGPT processes hundreds of millions of weekly queries with web browsing enabled. Perplexity is becoming a default research tool for B2B buyers. For a growing share of high-intent traffic, the AI’s answer is the search result — and if your business isn’t named in the answer, you’re invisible to that traffic.

The good news: AEO is mostly addressable. It’s content structure, schema, and authority signals — not a years-long climb up domain authority. Sites that take AEO seriously now have a real first-mover advantage as the practice matures.